A FAST AND RELIABLE MOTION HUMAN DETECTION AND TRACKING BASED ON BACKGROUND SUBTRACTION

According to the result of moving object detection research on video sequences, this paper proposes a new method to detect moving object based on background subtraction. First of all, we establish a reliable background updating model based on statistical and use a dynamic optimization threshold method to obtain a more complete moving object. And then,morphological filtering is introduced to eliminate the noise and solve the background disturbance problem. At last, contour projection analysis is combined with the shape analysis to remove the effect of shadow, the moving human body are accurately and reliably detected. The experiment results show that the proposed method runs quickly, accurately and fits for the real-time detection. The occlusion is one of the most common events in object tracking and object centroid of each object is used for detecting the occlusion and identifying each object separately. Video sequences have been captured in the laboratory and tested with the proposed algorithm. The algorithm works efficiently in the event of occlusion in the video sequences. Keywords-background subtraction; background model; moving object detection , shadow removal and occlusion detection.

• Publication year

  2012

• Venue

  IOSR Journal of Electronics and Communication Engineering

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.9790/2834-0112935
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Real-Time Detection and Tracking of Moving Object

  2008cited by this paper
• Object focused simultaneous estimation of optical flow and state dynamics

  2008cited by this paper
• A Moving Objects Detection Algorithm Based on Improved Background Subtraction

  2008cited by this paper
• Human body pose detection using Bayesian spatio-temporal templates

  2006cited by this paper
• An introduction to biometric recognition

  2004cited by this paper
• Illumination Insensitive Template Matching with Hyperplanes

  2003cited by this paper
• The Recognition of Human Movement Using Temporal Templates

  2001cited by this paper
• Algorithms for cooperative multisensor surveillance

  2001cited by this paper
• W4: Real-Time Surveillance of People and Their Activities

  2000cited by this paper
• Virtual Metamorphosis

  1999cited by this paper
• W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people

  1998cited by this paper
• Thresholding for change detection

  1998cited by this paper
• W4S: A real-time system detecting and tracking people in 2 1/2D

  1998cited by this paper
• The Representation and Recognition of Action Using Temporal Templates

  1997cited by this paper
• Image Segmentation in Video Sequences: A Probabilistic Approach

  1997cited by this paper
• Pfinder: real-time tracking of the human body

  1996cited by this paper
• Translation-tolerant mask matching using noncoherent reflective optics

  1968cited by this paper

• Thingspeak Based Monitoring IoT System for Counting People in A Library

  2018cites this paper
• Human Movement Tacking using Centroid Weighted Kalman Filter

  2016cites this paper
• Recent Trends in Computer Technology & Communication 2 k 16 " ( RTCTC-2 k 16 ) 33

  2016cites this paper
• Traffic road obstacles detection based on analysis of relative motion vectors

  2015cites this paper
• Real Time Moving Object Tracking In Video Processing

  2015cites this paper
• Recognition and Tracking of Occluded Objects in Dynamic Scenes

  2015cites this paper
• Review of Human Motion Detection based on Background Subtraction Techniques

  2015cites this paper
• Detection and Tracking of Moving Object: A Survey

  2015cites this paper
• Moving Object Segmentation using Enhanced Laplacian Thresholding Method for Video Surveillance

  2014cites this paper
• Real-Time Target Detection and Tracking: A Comparative In-depth Review of Strategies

  2013cites this paper